1. Field of the Invention
The present invention is directed to the field of graphical displays of database information. It is more particularly directed to managing the graphical display of a typically large number of data objects that efficiently presents mapped information about the relationship between the data objects that are stored in a relational database and that are used in on-line analytical processing.
2. Description of the Background Art
A computer-implemented database is a collection of data, organized in the form of tables. A table typically consists of columns that represent data of the same nature, and records that represent specific instances of data associated with the table. A relational database is a database that is typically a set of tables containing information that is manipulated in accordance with the relational model associated with the data. The product marketed under the trademarks IBM DB2 stores the data associated with the database in tables, and each table has a name.
On-Line Analytical Processing (OLAP) is a computing technique for summarizing, consolidating, viewing, analyzing, applying formulae to, and synthesizing data according to multiple dimensions. OLAP software enables users, such as analysts, managers, and executives, to gain insight into performance of an enterprise, such as a corporation, through rapid access to a wide variety of data dimensions that are organized to reflect the multidimensional nature of enterprise data, typically by means of hypotheses about possible trends in the data. More particularly, OLAP techniques may be used to analyze data from different viewpoints by identifying interesting associations in the information in a database. Therefore, OLAP is a decision support technique used in data management for the purpose of modeling and analyzing business information.
Data mining operations typically employ computer-based techniques to enable users to query structured data stored in computers in forms such as: multidimensional databases, conventional databases, or flat computer files. More particularly, data mining involves extracting computer-based information and enables a user to discover trends about the computer-based information.
An increasingly popular data model for OLAP applications, such as data mining, is the multidimensional database (MDDB). Often, data analysts use MDDBs during interactive exploration of business data for finding regions of anomalies in the data. Before this data can be explored, modeling needs to be enabled for the business. Modeling a business for an OLAP application may require large amounts of metadata including data entities.
In the past graphics tools have used objects, such as rectangle displays, to represent data entities, such as relational database tables. The objects are displayed so that they present the relationships between the data contained in the relational database tables. There has been a problem representing the OLAP systems associated with the data while simultaneously representing the relational database data structures associated with the storage of the data. For instance, data that is stored in a relational database is typically stored in the form of two-dimensional tables. While, OLAP data representation typically includes dimensional and measure data representation, relational database information is represented in the two-dimensional table format. Presentations in the past have attempted to show the mapping between the relational tables used to store the data and the OLAP objects that are presented for OLAP data analysis.
Representing the mapping of OLAP data to relational database data is difficult. Often, OLAP dimensional data objects are comprised of a plurality of relational database tables, and the plurality of relational database tables may include some of the same tables. By means of example OLAP data may include the number of sales that is measure data and also dimensional data about the type of products that were sold, the time frame of the sales, and the geographical market for the sales. In the past, representation of such data might include multiple references to relational database tables that are used to represent a dimension or a measure.
Given the large amount of OLAP data associated with the plurality of tables in databases, such as multidimensional databases and relational databases, the related graphical representation may require a typically large number of objects. Therefore, there may be many confusing representations of OLAP dimensions and measures when the mapped relational database table references are replicated to represent all their associations to OLAP dimensions and measures. This requires the data analyst to understand the complicated mapping structure in order to review information about the OLAP objects within the graphical display during analysis of OLAP data.
It would therefore be useful to be able to analyze typically large amounts of entity information with a graphical display that efficiently presents the mapping between the OLAP objects and the related relational database tables. When employing OLAP processing techniques it would be useful to be able to efficiently analyze multidimensional data with a graphical display that minimizes the disadvantages associated with current graphical displays. Graphical presentations in the past have not adequately displayed the mapping between the relational tables used to store the data and the OLAP objects that are presented for OLAP data analysis.
From the foregoing it will be apparent that there is still a need to improve the graphical display of a typically large number of objects so that the mapping between OLAP objects and related relational database tables is efficiently presented in order to enhance analysis of the objects and the associated data.